Abstract
The freeze–thaw cycle is one of the major sources of damage to granular-surfaced roadways, especially in areas where the timing of heavy agricultural traffic coincides with that of spring thawing. To help local roads agencies plan better for annual budgets and frost embargos, it is useful to be able to predict the frost depth and number of freeze–thaw cycles under a given roadway based on continually updated weather and soil data. Computational modeling can help in this regard, and may be conducted by collecting data on weather and the thermal and hydraulic properties of the soil, as well as soil temperature, moisture, and suction, and using the data directly in the analyses. In order to obtain accurate field data for model calibrations and predictions, an appropriate sensor network and data acquisition system must be carefully planned and installed. This article details the development and installation procedures for one such system of sensors for subgrade temperature, water content, and matric suction, and presents lessons learned throughout the process. Various issues are discussed relating to selection of the sensor and data acquisition system, laboratory and field checks, borehole sensor installation tools, and post-installation troubleshooting and monitoring. To ensure a successful installation beneath the granular roadway, laboratory and field trials were first performed. Salient details of a pilot installation in Hamilton County, IA are provided to guide others developing and scaling similar subgrade sensor systems.
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